Multi-objective optimal design of hybrid composite laminates under eccentric loading

Abstract

Laminated composites are being used in many engineering applications since they provide significant weight reduction, better fatigue and corrosion resistance. In this study, design optimization of a hybrid composite laminate subjected to eccentric loading was carried out using multi-objective genetic algorithm (MOGA). The ply material (carbon fiber or E glass) and fiber orientations (−90 ≤ θ ≤ 90) were considered as design variables. The objective function was to minimize cost and weight with the maximization of the stiffness. The design constraints were the maximum Tsai-Wu failure index, first mode natural frequency. The numerical analyses were carried out by using ANSYS software package. Genetic aggregation model was used to generate the response surfaces which were used to obtain the optimum design variables. The optimum lay-up sequence and ply materials were determined for weight saving and cost reduction of hybrid composite plates. It was shown that the hybridization of carbon fiber and E glass fiber provided the optimal designs offers lower cost and higher mechanical performance. MOGA method was very effective to optimize the structural performance of the hybrid composite plates under eccentric loading.

Keywords

• Genetic algorithms
• Hybrid composites
• Optimization
• Eccentric loading